Demonstrating Surrogacy of Animal Diversity with Plant Diversity and Their Integration to Assess Inclusive Biodiversity: A Geoinformatics Basis

Abstract

Characterizing biological richness at the landscape level is conveniently done using the plant as an indicator of biota. The congruence between plant and animal biological richness (BR) was studied by extending the scope of methodology from past studies in order to understand the question; does higher plant richness encourages higher animal richness? Using satellite images, 16 forest vegetation classes to integrate BR attributes for 85 plants and 271 animal species were derived. Plant BR analysis linked six biodiversity attributes (i.e., spatial, phytosociological, social, physical, economic and ecological) together based on their relative importance. The information of four terrestrial animal taxa (i.e., mammal, bird, reptile and amphibian) from various resources was utilized over five surrogates of biological richness (habitat suitability, spatial heterogeneity, eco-climatic stability, plant structural properties, and forage). A methodological basis of spatial enumeration of animal richness was provided in one of the most biologically rich landscapes of India, forming part of Indian Gangetic plains. It was observed that positive congruence between BR of plant and animal with a spatial overlap of 82.23% for the inclusive BR. Significant positive correlation (R 2 : 0.7) was observed for high BR values (7–9) of animal and plant. Authors believe the strengths of our study are (i) translation of animal characterization onto a spatial map, (ii) collection and utilization of scattered data of animals from varied resources for Indian region where proper documentation is lacking (iii) generation of an inclusive BR map having higher conservation potential, and (iv) creation of a database having retrieval and future modification capability. This methodology has the potential for inclusive plant and animal biological richness for effective conservation implications with more site-specific data of a wider range of animals.